v a r P r i o - version 0.4

Introduction

varPrio is a tool for the prioritization of genetic variants from WES/WGS data. Variants which are relevant and associated to the disease phenotype are prioritized based on in silico predictions of damaging mutations and based on occurrence or frequency across pedigrees and in the population. varPrio is developed as part of the Accelerator program for Discovery in Brain disorders using Stem cells (ADBS) at NCBS. Please read the README file before using this program.

Requirements

1. python version 2.7

2. python packages NumPy, pandas, os, glob, argparse. To install them,

    pip install numpy pandas os glob argparse
   

Usage

usage: varprio-0.4.py [-h] -T {snp,indel} -I INPUTFILEINFO -PC
	                POPULATIONCONTROL -AFC ALLFAMILYCONTROL -O OUTDIR

varPrio version 0.4

optional arguments:
  -h, --help            show this help message and exit
  -T {snp,indel}, --typeofvariant {snp,indel}
	                  Type of variant to prioritize {snp,indel}
  -I INPUTFILEINFO, --inputfileinfo INPUTFILEINFO
	                  Path to the text file containing 3 rows. 1st row -
	                  Sample identifier of the affected individuals; 2nd row
	                  - Family identifier; 3rd row - Path to the annotated
	                  file (ANNOVAR tab delimmited TXT files).
  -PC POPULATIONCONTROL, --populationcontrol POPULATIONCONTROL
	                  Path to population control variant data file.
  -AFC ALLFAMILYCONTROL, --allfamilycontrol ALLFAMILYCONTROL
	                  Path to all familial control variant data file of
	                  multiple families.
  -O OUTDIR, --outdir OUTDIR
	                  Path to the output directory where the varprio results
	                  will be written.

Please give absolute(full) path to all the files. 

Note: vpr format is the varPrio format just to distinguish the varPrio results from other files.

How to Cite?

Please cite the following article:

Suhas Ganesh, Husayn Ahmed P, Ravi K Nadella, Ravi P More, Manasa Sheshadri, Biju Viswanath, Mahendra Rao, Sanjeev Jain, The ADBS consortium, Odity Mukherjee. 2018. Exome sequencing in families with severe mental illness identifies novel and rare variants in genes implicated in Mendelian neuropsychiatric syndromes. Psychiatry and Clinical Neurosciences. doi: 10.1111/pcn.12788

License

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

How does varPrio work?

varPrio is a tool for the prioritization of genetic variants from whole genome/exome sequencing data of pedigrees.

Variants are prioritized if –

(a) the variant is found to be shared by all affected individuals within the pedigree while allowing for one missing genotype;

(b) the variant fell into any of the following deleterious categories – Non-Synonymous Damaging Strict (NSD-S) set predicted to be damaging by 5 prediction algorithms - SIFT (Kumar et al., 2009), Polyphen-2 HDIV (Adzhubei et al., 2010), Mutation taster2 (Schwarz et al., 2014), Mutation assessor (Reva et al., 2011) and LRT (Chun and Fay, 2009); Disruptive set predicted to result in protein truncation (splice site, stop gain or stop loss variants) or Non-Synonymous Damaging Broad (NSD-B) set predicted to be damaging by one or more of the above stated 5 prediction algorithms;

Indels are prioritized if they are frameshift insertion/deletion, stopgain or stoploss.

The information about the presence/absence and frequency of the variant in the population control information provided will be added to the final prioritized files.

Instructions

1. The folder "example_files" contains a set of input files in the required format for varPrio. The variants file contain variants only from chromosome 19 as an example. This folder also contains output files generated by varPrio.

2. Create a file detailing the information about input variant files (INPUTFILEINFO) This file contains 3 rows. 1st row - Sample identifier of the affected individuals; 2nd row - Family identifier; 3rd row - Path to the annotated file (ANNOVAR tab delimmited TXT files). This program is tailor-made for large-scale analysis of pedigrees recruited in ADBS. The input formats recognized by this tool is based on the files generated in ADBS. This tool is not generalized to read any type of annotated VCFs.

3. Provide counts of variants in population controls and familial controls (POPULATIONCONTROL and ALLFAMILYCONTROL) These files 3 rows: chr, pos and count

4. Create output directory in which you need varPrio to write the results to.

Example commands

mkdir ./example_files/output_snp
mkdir ./example_files/output_indel

python varprio-0.4.py -T snp \
	-I /home/husayn/varPrio-0.4/example_files/input_info_snp.txt \
	-PC /home/husayn/varPrio-0.4/example_files/INDEX-db_phase1_snp_population_control_chr19.txt \
	-AFC /home/husayn/varPrio-0.4/example_files/All_fam_control_count.txt \
	-O /home/husayn/varPrio-0.4/example_files/output_snp 

python varprio-0.4.py -T indel \
	-I /home/husayn/varPrio-0.4/example_files/input_info_indel.txt \
	-PC /home/husayn/varPrio-0.4/example_files/INDEX-db_phase1_indel_population_control_chr19.txt \
	-AFC /home/husayn/varPrio-0.4/example_files/All_fam_control_count.txt \
	-O /home/husayn/varPrio-0.4/example_files/output_indel 

Output files

1. Results of every step is written to a separate file. This helps in customizing prioritization approach as per the requirement.

2. In the case of SNP, the final files are "LIST2A_step3_1to5P_withPCAFC.vpr" and "LIST2B_step3_1to5P_withPCAFC.vpr". These contain prioritized variants as described above.

3. Five new columns are added to the output files. These contain sampleID, pedigreeID, number of algorithms calling it damaging, occurrence/count in population controls and occurrence/count in familial controls respectively.

4. While the LIST2B contains all columns provided by the ANNOVAR annotation, LIST2A contains only selected columns required in the context of ADBS downstream analysis.

5. In the case of INDELs, "step2_prioritized_INDEL_LIST3.vpr" is the final prioritized list of variants. Three new columns are added in the output files, containing sampleID, pedigreeID, presence/absence in the population controls.

Column headers of "LIST2B_step3_1to5P_withPCAFC.vpr":

Chr Start End Ref Alt Func.refGene Gene.refGene GeneDetail.refGene ExonicFunc.refGene AAChange.refGene cytoBand genomicSuperDups esp6500siv2_all 1000g2015aug_all 1000g2015aug_eur ExAC_ALL ExAC_AFR ExAC_AMR ExAC_EAS ExAC_FIN ExAC_NFE ExAC_OTH ExAC_SAS avsnp147 SIFT_score SIFT_pred Polyphen2_HDIV_score Polyphen2_HDIV_pred Polyphen2_HVAR_score Polyphen2_HVAR_pred LRT_score LRT_pred MutationTaster_score MutationTaster_pred MutationAssessor_score MutationAssessor_pred FATHMM_score FATHMM_pred PROVEAN_score PROVEAN_pred VEST3_score CADD_raw CADD_phred DANN_score fathmm-MKL_coding_score fathmm-MKL_coding_pred MetaSVM_score MetaSVM_pred MetaLR_score MetaLR_pred integrated_fitCons_score integrated_confidence_value GERP++_RS phyloP7way_vertebrate phyloP20way_mammalian phastCons7way_vertebrate phastCons20way_mammalian SiPhy_29way_logOdds Otherinfo1 Otherinfo2 Otherinfo3 Otherinfo4 Otherinfo5 Otherinfo6 Otherinfo7 Otherinfo8 Otherinfo9 Otherinfo10 Otherinfo11 Otherinfo12 Otherinfo13 Sample_ID Pedigree_ID Predicted_deleterious_by PC_Count AFC_Count

Column headers of "LIST2A_step3_1to5P_withPCAFC.vpr":

Chr Start Ref Alt Func.refGene Gene.refGene ExonicFunc.refGene AAChange.refGene 1000g2015aug_all ExAC_ALL ExAC_SAS avsnp147 SIFT_pred Polyphen2_HDIV_pred LRT_pred MutationTaster_pred MutationAssessor_pred Sample_ID Pedigree_ID Predicted_deleterious_by PC_Count AFC_Count

Column headers of "step2_prioritized_INDEL_LIST3.vpr":

Chr Start End Ref Alt Func.refGene Gene.refGene GeneDetail.refGene ExonicFunc.refGene AAChange.refGene cytoBand genomicSuperDups esp6500siv2_all 1000g2015aug_all 1000g2015aug_eur ExAC_ALL ExAC_AFR ExAC_AMR ExAC_EAS ExAC_FIN ExAC_NFE ExAC_OTH ExAC_SAS avsnp147 SIFT_score SIFT_pred Polyphen2_HDIV_score Polyphen2_HDIV_pred Polyphen2_HVAR_score Polyphen2_HVAR_pred LRT_score LRT_pred MutationTaster_score MutationTaster_pred MutationAssessor_score MutationAssessor_pred FATHMM_score FATHMM_pred PROVEAN_score PROVEAN_pred VEST3_score CADD_raw CADD_phred DANN_score fathmm-MKL_coding_score fathmm-MKL_coding_pred MetaSVM_score MetaSVM_pred MetaLR_score MetaLR_pred integrated_fitCons_score integrated_confidence_value GERP++_RS phyloP7way_vertebrate phyloP20way_mammalian phastCons7way_vertebrate phastCons20way_mammalian SiPhy_29way_logOdds Otherinfo1 Otherinfo2 Otherinfo3 Otherinfo4 Otherinfo5 Otherinfo6 Otherinfo7 Otherinfo8 Otherinfo9 Otherinfo10 Otherinfo11 Otherinfo12 Otherinfo13 Sample_ID Family PC

Contact

For technical queries, please write to husaynp@ncbs.res.in

Contributors

Developed by: Husayn Ahmed P

Conceptualized by: Suhas Ganesh, Husayn Ahmed P, Odity Mukherjee

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